Sr. Application & Technical Architect - Data Warehouse/Analytics

We are seeking a Senior Data & Analytics Architect to lead a large-scale Enterprise Data Warehouse (EDW), reporting, and analytics modernization initiative. This is a hands-on architecture leadership role responsible for defining technical strategy, solution architecture, modernization roadmaps, and engineering execution across enterprise data, reporting, and analytics platforms. Key Responsibilities

• Lead end-to-end architecture for enterprise data warehouse, reporting, analytics, and data integration solutions.
• Drive modernization of legacy ETL processes, SQL code, Unix/Linux scripts, and manual workflows into scalable Python-based solutions and automation frameworks.
• Translate complex business, operational, and regulatory requirements into scalable and maintainable technical designs.
• Design architecture across databases, APIs, application services, orchestration, scheduling, security, monitoring, and cloud platforms.
• Build proof-of-concepts and evaluate technology options to support architectural decision-making.
• Lead enterprise reporting and analytics initiatives, including data quality, reconciliation, drill-down reporting, and reporting modernization.
• Establish engineering best practices utilizing Azure DevOps, CI/CD pipelines, source control, code review processes, and deployment automation.
• Partner with infrastructure, cloud, security, analytics, and engineering teams to deliver enterprise-scale solutions.
• Develop architecture diagrams, technical specifications, implementation plans, operational models, and modernization roadmaps.
• Mentor architects, engineers, ETL developers, BI developers, analysts, and testers.
• Present technical recommendations, risks, and strategic solutions to executive leadership and key stakeholders., Preferred Technical Stack
• Python
• SQL
• Azure
• Azure Data Factory (ADF)
• Databricks
• Snowflake
• Teradata
• Informatica
• Power BI
• Tableau
• BusinessObjects
• Azure DevOps
• CI/CD
• Data Warehousing
• Analytics
• Data Integration
• Enterprise Architecture

Additional Requirements

• 12+ month contract opportunity.
• 100% remote position.
• Candidates must reside within the Continental United States.
• Candidates must be authorized to work in the United States without sponsorship.
• Not open to third-party firms, consulting companies, C2C arrangements, or vendor submissions.
• Direct applicants only.

Why Join Us

• Lead enterprise-scale data and analytics modernization initiatives.
• Influence architecture strategy and technology direction.
• Work with modern cloud and data platforms.
• Drive transformation from legacy technologies to scalable, automated solutions.
• Collaborate with senior leadership and high-performing technical teams.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent professional experience.
• 10+ years of experience in Data Architecture, Analytics Architecture, Solution Architecture, or Enterprise Architecture roles.
• Proven success architecting and delivering enterprise data warehouse, analytics, reporting, and transaction-processing solutions.
• Strong hands-on Python development experience.
• Advanced SQL development, optimization, and troubleshooting expertise.
• Experience designing data-intensive applications, APIs, databases, security frameworks, job scheduling, and monitoring solutions.
• Experience with enterprise BI and reporting tools such as Power BI, Tableau, BusinessObjects, SAS, or similar platforms.
• Experience implementing Azure DevOps, Git-based source control, branching strategies, CI/CD pipelines, and automated deployment processes.
• Experience leading cross-functional engineering and analytics teams.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Healthcare payer, Medicaid, managed care, or health insurance experience.
• Experience supporting CMS, Medicaid, regulatory, or federal reporting initiatives.
• Experience with cloud migration and modernization programs.
• Hands-on experience with Azure, Azure Data Factory, Databricks, Azure Data Lake Storage, Snowflake, or similar cloud data platforms.
• Experience with Informatica, Teradata, or enterprise ETL and data integration technologies.
• Strong data modeling experience, including conceptual, logical, physical, dimensional, and transactional models.
• Experience leveraging AI-assisted engineering, automation, testing, or code conversion within enterprise environments.
• Knowledge of HIPAA, PHI, PII, and regulated data environments.